Experimental investigation of energy consumption and model identification of reverse osmosis desalination system fed by hybrid renewable energy source under different operating conditions

Hossam-Eldin, Ahmed A.; Abed, Kamal; Youssef, Karim Hassan; Kotb, Hossam

doi:10.1002/tee.22943

Cited by 2 publications

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…10 and 13, for the corresponding head. Other effects on the characteristics of outflow in the membranes, such as those provoked by the variation of the water temperature or the oscillation of the rotation frequency, were not considered in this work and may be consulted in [23,24].…”

Section: Mathematical Model To Obtain the Head Versus The Flowrate Curve Required By The Systemmentioning

confidence: 99%

A methodology to obtain the performance curves of windmills associated with piston pumps: application in water desalination systems by reverse osmosis

Matos

Palombella

Dantas

et al. 2021

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

The use of windmills for the pumping of well water has appeared economically feasible in regions with average winds above 5 m/s, and when the water is used for human consumption and irrigation in arid rural zones, the importance of extracting the water from these wells efficiently and sustainably becomes more evident. However, concerning the state of Ceará/Brazil, only 18% of the drilled wells are freshwater wells, thus requiring additional energy for the utilization of desalination systems such as reverse osmosis. For that, the correct sizing of the pumping system associated with water desalination systems is essential, bearing in mind that the knowledge of the performance curves of the windmills, usually associated with piston pumps, is the "key factor" of the project. A brief analysis of the literature and websites of windmill suppliers shows that the performance curves of windmills associated with piston pumps are scarce, and the procedure to obtain them is not clear. This work's novelty is to use the windmill's power coefficient curve in association with the piston pumps to obtain the windpump performance curves, as pressure head versus volumetric flow rate in different wind conditions and sizes of windmills. The obtained curves were compared with other two curves found in the literature: one in a supplier's catalog and another from the "rule of thumb". The results showed a considerable divergence when calculating the root mean square deviation: 43.73% in relation to the supplier data average, and 125.76% in relation to the rule of thumb average results; however, the model proposed herein presented a limited operational range, which was not verified in the other two curves, which reproduced unlimited machines in terms of provided pressure head and flow rate. The unreal and asymptotic characteristics are more evident in the curves obtained by the rule of thumb, where the differences are also greater (125.76%) in relation to the proposed model. In terms of freshwater production, the model proposed herein reached, with an average wind speed of 6.5 m/s, and with a windmill of 6.1 m in diameter, a flow rate of up to 9.1 m 3 /day, after going through the reverse osmosis system. The same condition with the rule of thumb's model reached a flow rate of up to 11.3 m 3 /day. Finally, the model proposed herein for obtaining windmill's performance curves proved to be easy to implement and with realistic results, becoming an important design tool.

show abstract

Section: Mathematical Model To Obtain the Head Versus The Flowrate Curve Required By The Systemmentioning

confidence: 99%

A methodology to obtain the performance curves of windmills associated with piston pumps: application in water desalination systems by reverse osmosis

Matos

Palombella

Dantas

et al. 2021

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods

Golabi,

Erradi,

Qiblawey

et al. 2024

Appl Intell

View full text Add to dashboard Cite

The reverse osmosis (RO) process is a well-established desalination technology, wherein energy-efficient techniques and advanced process control methods significantly reduce production costs. This study proposes an optimal real-time management method to minimize the total daily operation cost of an RO desalination plant, integrating a storage tank system to meet varying daily freshwater demand. Utilizing the dynamic model of the RO process, a cascade structure with two reinforcement learning (RL) agents, namely the deep deterministic policy gradient (DDPG) and deep Q-Network (DQN), is developed to optimize the operation of the RO plant. The DDPG agent, manipulating the high-pressure pump, controls the permeate flow rate to track a reference setpoint value. Simultaneously, the DQN agent selects the optimal setpoint value and communicates it to the DDPG controller to minimize the plant’s operation cost. Monitoring storage tanks, permeate flow rates, and water demand enables the DQN agent to determine the required amount of permeate water, optimizing water quality and energy consumption. Additionally, the DQN agent monitors the storage tank’s water level to prevent overflow or underflow of permeate water. Simulation results demonstrate the effectiveness and practicality of the designed RL agents.

show abstract

Experimental investigation of energy consumption and model identification of reverse osmosis desalination system fed by hybrid renewable energy source under different operating conditions

Cited by 2 publications

References 16 publications

A methodology to obtain the performance curves of windmills associated with piston pumps: application in water desalination systems by reverse osmosis

A methodology to obtain the performance curves of windmills associated with piston pumps: application in water desalination systems by reverse osmosis

Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods

Contact Info

Product

Resources

About